Neuroscience 2005 Abstract
| Presentation Number: | 137.5 |
|---|---|
| Abstract Title: | Reconstruction and analysis of human V1 by imaging the stria of Gennari using MRI at 7T. |
| Authors: |
Hinds, O. P.*1
; Polimeni, J. R.2
; Blackwell, M. L.4
; Wiggins, C. J.4
; Wiggins, G. C.4
; van der Kouwe, A. J. W.4
; Wald, L. L.4
; Schwartz, E. L.1,2,3
; Fischl, B.4,5
1Cog & Neural Syst, Boston Univ., Boston, MA 2Elec & Comp Eng, Boston Univ., Boston, MA 3Anat & Neurobiol, Boston Univ., Boston, MA 4MA, 677 Beacon St., 02215, 5USA, 677 Beacon St., 02215, |
| Primary Theme and Topics |
Sensory and Motor Systems - Vision -- Visual cortex: Functional organization and circuitry |
| Secondary Theme and Topics | Techniques in Neuroscience<br />- Staining, Tracing, and Imaging Techniques |
| Session: |
137. Visual Cortex: Architecture and Circuitry I Slide |
| Presentation Time: | Sunday, November 13, 2005 9:00 AM-9:15 AM |
| Location: | Washington Convention Center - Room 204A |
| Keywords: | Visual Cortex, V1 Anatomy, Ex Vivo Imaging, Surface Reconstruction |
The stria of Gennari --a definitive landmark for anatomical identification of primary visual cortex--has been imaged both ex vivo and in vivo and visualized in planar sections, but no surface reconstructions were performed. To image the stria, we used a high-bandwidth, multiecho FLASH pulse sequence with an isotropic voxel size of 200 microns and scanned ex vivo human occipital cortex at 7T for 12 hours. This provided enhanced contrast between gray and white matter and reduced MR image distortion, thus enabling reliable identification of the full extent of the stria. We developed software for reconstructing surfaces from slice images obtained either from MRI or serial tissue section data. This software was used to identify vertices representing points of the stria as input to a surface tiling algorithm, which outputs a two-dimensional, manifold triangular mesh representing the striate surface. A flattened surface was obtained using an accurate quasi-isometric flattening algorithm (see Balasubramanian et al., this meeting), using a global error measure based on geodesic distances for a minimal error brain flattening. Surface-based representations of V1 are necessary for quantifying the shape, surface area, and inter-subject variability of V1, supplying ground-truth for probabilistic atlases used for cross-subject registration, and may provide a method for same-subject comparison to functionally determined V1 in vivo. A software toolkit is available supporting the surface reconstruction methods described in this work.
Supported by NIH/NIBIB EB001550, NCRR P41-RR14075, RR16594-01A1, BIRN002, and U24 RR021382, and the MIND Institute
Sample Citation:
[Authors]. [Abstract Title]. Program No. XXX.XX. 2005 Neuroscience Meeting Planner. Washington, DC: Society for Neuroscience, 2005. Online.
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